[Ml-stat-talks] Wilks Statistics Seminar: Jun Liu, March 1 at 12:30 PM, Sherrerd Hall 101
Ahmet Emre Barut
abarut at Princeton.EDU
Mon Feb 25 17:50:25 EST 2013
=== ORFE - Wilks Statistics Seminar Announcement ===
DATE: Friday, March 1, 2013
LOCATION: Sherrerd Hall 101
SPEAKER: Jun Liu, Department of Biostatistics, Harvard University
TITLE: Bayesian View of Sliced Inverse Regression with Interaction Detection
ABSTRACT: Previously we have proposed a Bayesian partition model for detecting interactive variables in a classification setting with discrete covariates. This framework takes advantage of the structure of the naïve Bayes classifier and introduces latent indicator variables for selecting variables and interactions. In our effort to extend the methods to continuous covariates, we found interesting connections with semi-parametric index models and the Sliced Inverse Regression method. In index models, the response is influenced by the covariates through an unknown function of several linear combinations of the predictors. Our finding of the Bayesian formulation of such models enabled us to propose a set of new models and methods that can effectively discover second-order effects and interactions among the covariates. A two-stage stepwise procedure based on likelihood ratio test is developed to select relevant predictors and a Bayesian model with dynamic slicing scheme is derived. The performance of the proposed procedure in comparison with some existing method is demonstrated through simulation studies.
Joint work with Bo Jiang.
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